[R] looking for a smarter way

[Bliese, Paul D MAJ WRAIR-Wash DC]

It looks like you've solved this problem, but another nice solution is to
use the aggregate command as in:

xtap<-aggregate(xcmd[,1:5],list(xclu$clustering),var)

I'm not sure why R requires one to explicitly provide a list as the second
argument if the second arguement is a vector (this is not necessary in
SPLUS), but this is a minor issue....



-----Original Message-----
From: Grum, Mikkel [mailto:M.GRUM at CGIAR.ORG]
Sent: Tuesday, August 21, 2001 3:15 AM
To: R-help at lists.R-project.org
Subject: [R] looking for a smarter way


I have two problems where I've come up with some code that will do the
analysis that I want, but it looks pretty clumsy.  In the first case, I
calculate the variance on five different columns for each of 14 clusters and
get them into one matrix.  I get the job done, but I would have thought that
it could be done in one or two lines, not six, and be generalized so that it
didn't matter how many columns I had.  Any suggestions?

xtap1<-tapply(xcmd[,1],xclu$clustering,var)
xtap2<-tapply(xcmd[,2],xclu$clustering,var)
xtap3<-tapply(xcmd[,3],xclu$clustering,var)
xtap4<-tapply(xcmd[,4],xclu$clustering,var)
xtap5<-tapply(xcmd[,5],xclu$clustering,var)
xtap<-cbind(xtap1,xtap2,xtap3,xtap4,xtap5)


The next example is somewhat similar, but I'm trying to calculate a
Shannon-weaver information index for each cluster based on the proportion of
objects with each "local.name".  I start by tabulating the frequency of
presence of each local.name in each cluster.  The code does what I want, but
I have other examples where I have hundreds of clusters and I would prefer
not to have to type in a line for each cluster.  Again, there must be a way
and I would appreciate any suggestions:

xtab<-table(x$LOCAL.NAME,xclu$clustering)
xshw1<--sum((xtab[,1]+0.000001)/sum(xtab[,1])*(log((xtab[,1]+0.000001)/sum(x
tab[,1]))))
xshw2<--sum((xtab[,2]+0.000001)/sum(xtab[,2])*(log((xtab[,2]+0.000001)/sum(x
tab[,2]))))
xshw3<--sum((xtab[,3]+0.000001)/sum(xtab[,3])*(log((xtab[,3]+0.000001)/sum(x
tab[,3]))))
xshw4<--sum((xtab[,4]+0.000001)/sum(xtab[,4])*(log((xtab[,4]+0.000001)/sum(x
tab[,4]))))
xshw5<--sum((xtab[,5]+0.000001)/sum(xtab[,5])*(log((xtab[,5]+0.000001)/sum(x
tab[,5]))))
xshw6<--sum((xtab[,6]+0.000001)/sum(xtab[,6])*(log((xtab[,6]+0.000001)/sum(x
tab[,6]))))
xshw7<--sum((xtab[,7]+0.000001)/sum(xtab[,7])*(log((xtab[,7]+0.000001)/sum(x
tab[,7]))))
xshw8<--sum((xtab[,8]+0.000001)/sum(xtab[,8])*(log((xtab[,8]+0.000001)/sum(x
tab[,8]))))
xshw9<--sum((xtab[,9]+0.000001)/sum(xtab[,9])*(log((xtab[,9]+0.000001)/sum(x
tab[,9]))))
xshw10<--sum((xtab[,10]+0.000001)/sum(xtab[,10])*(log((xtab[,10]+0.000001)/s
um(xtab[,10]))))
xshw11<--sum((xtab[,11]+0.000001)/sum(xtab[,11])*(log((xtab[,11]+0.000001)/s
um(xtab[,11]))))
xshw12<--sum((xtab[,12]+0.000001)/sum(xtab[,12])*(log((xtab[,12]+0.000001)/s
um(xtab[,12]))))
xshw13<--sum((xtab[,13]+0.000001)/sum(xtab[,13])*(log((xtab[,13]+0.000001)/s
um(xtab[,13]))))
xshw14<--sum((xtab[,14]+0.000001)/sum(xtab[,14])*(log((xtab[,14]+0.000001)/s
um(xtab[,14]))))
xshw<-rbind(xshw1,xshw2,xshw3,xshw4,xshw5,xshw6,xshw7,xshw8,xshw9,xshw10,xsh
w11,xshw12,xshw13,xshw14)
xtap<-cbind(xtap1,xtap2,xtap3,xtap4,xtap5,(xtapx<-(xtap1+xtap2+xtap3+xtap4+x
tap5)),xshw)


Thanks a lot in advance!!

Mikkel






Mikkel Grum, PhD
Genetic Diversity Scientist
International Plant Genetic Resources Institute (IPGRI)
Sub-Saharan Africa Group
***
c/o ICRAF
PO Box 30677 Nairobi, Kenya
m.grum at cgiar.org
ipgri-kenya at cgiar.org
www.ipgri.cgiar.org

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